CQC Insight 15: Ethnicity data recording in mental health

In this article, we look at the quality of ethnicity data recording for mental health services within local health and care systems.

Background

Our 2020/21 annual State of Care report highlighted the impact of the pandemic on people’s mental health. This included the increased demand for services. We also shone a light on the fact that the pandemic has not affected everyone equally. For example, some people from deprived areas and people from Black and minority ethnic groups have been affected more.

As highlighted in State of Care, according to Public Health England, at the end of May 2021 the cumulative age-standardised mortality rate in the most deprived areas in England was 2.4 times the rate in the least deprived areas. The mortality rates in people from the Black and Asian groups were more than double the rate in people from the White group.

Inequality in care was also highlighted by the findings of our provider collaboration review on children and young people’s mental health. Again, this showed that the COVID-19 pandemic has demonstrated the inequalities faced by some people with mental health needs. In some cases, the pandemic made these inequalities worse.

Concerns around inequalities in mental health care were also highlighted by NHS Digital’s annual figures on the Mental Health Act, published in October 2021.

Not being able to access the right care and support at the right time increases the risk of an individual’s mental health deteriorating.

Health inequalities are a significant and long-standing concern for the NHS, with preventing inequality a key feature of the NHS Long Term Plan.

Some systems in our provider collaboration review told us how they were trying to address these inequalities. For example, some areas told us they were now working together better to identify children and young people who need mental health care and support. This included people from Black and minority ethnic groups, Travellers, and asylum seekers.

But we found that tackling inequalities was often not a main priority for systems. While some areas were using equalities monitoring data to identify children and young people in need of mental health support, the data was not always captured well. As a result, we were concerned that this could lead to missed opportunities to adapt care to meet the needs of individuals and local populations.

Quality of ethnicity recording in mental health data sets

Reliable, quality evidence is a fundamental tool in identifying, tackling and improving service equality.

In June 2021, the Nuffield Trust and NHS Race and Health Observatory published their report on Ethnicity coding in English health service datasets. This identified substantial data quality issues with many health datasets for hospitals and community health care. In particular, the report highlighted concerns that a large proportion of data was not linked to a known patient ethnicity. It also reported a notable and growing reliance on ‘not known’ and ‘not stated’ ethnicity codes. Without this information, health providers will not be able to use the data effectively to monitor equality and detect inequalities in access to services and outcomes.

The report recommended that assessing the quality of ethnicity coding should be made part of our inspections and ratings. Publishing this report is a first step in our work to consider how we can use quality of ethnicity data recording in our regulation.

Building on the findings from this report, and following the concerns raised in our provider collaboration review on mental health around data on ethnicity, we have looked at the quality of ethnicity coding for mental health services who report to the Mental Health Services Data Set (MHSDS). To do this, we analysed a sample of the MHSDS ethnicity data from June 2019 to May 2021.

In line with the national mandatory standard, the MHSDS data set groups ethnicity into 16+1 ethnic data categories. These have been grouped into the following categories for the purposes of this analysis:

• Asian and Asian British
• Black and Black British
• Mixed
• White
• Other
• Not known – ethnicity is missing or otherwise not known
• Not stated – an individual chooses not to give their ethnicity.

Similarly to the report of the NHS Race and Health Observatory, we found that there was a substantial and growing proportion of patients whose ethnicity was recorded as ‘not known’ and ‘not stated’. In the most recent month analysed (May 2021), we found that the ethnicity of nearly one in six patients (15.2%) was recorded under these categories (figure 1).

It is not clear why these categories have increasingly been reported. It is possible that the unprecedented demands of COVID-19 on health services may have reduced staff ability to make sure they are being recorded appropriately.

Systems with higher rates of not known and not stated will not be able to effectively understand, and in turn address, inequalities in the care being provided. How much the ‘not known’ and ‘not stated’ categories for recording ethnicity are used varies across integrated care systems. Together, use of these categories ranges from 4.8% to 29.5% (figure 2). Which code is used also varies across systems. For example, some integrated care systems tend to report greater levels of ‘not known’, while others report greater levels of ‘not stated’.

Why recording varies across systems is unclear. But local demographics, policy and leadership may all play a role. To try and explore this further, we looked at the use of ‘not known’ and ‘not stated’ categories against the ethnic diversity of each system’s local population (figure 3). While areas with the lowest proportion of the population identifying as White (7 out of 42) tended to have lower rates of MHSDS records with ethnicity recorded as “not known” or “not stated”, the analysis found no clear correlation between ethnic diversity and rates of data completion. We will continue to carry out work to better understand how the quality of ethnicity recording relates to other information we hold about quality at provider and ICS level.

We are concerned that poor recording of ethnicity, and an overreliance on the categories of ‘not known’ and ‘not stated’, is masking equality issues. Poor-quality recording makes it more difficult for organisations to interrogate and use data to address potential inequalities and that services are meeting the needs of individuals. For mental health services, this will reduce their ability to understand variation in referrals, treatments and deaths by ethnicity.

As highlighted in our provider collaboration review of children and young people’s mental health services, looking forward, it is important for systems to continue to increase their focus on addressing health inequalities. We encourage services to support system-wide efforts in tackling existing, and preventing future, health inequalities by improving how data to monitor equalities is captured and used, and improving training for staff on coding.

However, this needs to be part of a system-wide approach. As highlighted in the report by the Nuffield Trust and NHS Race and Health Observatory and a King’s Fund report on Ethnicity coding in health records, a key element will be updating guidance on recording of ethnicity as current guidelines were published in 2001.